Modeling complex logistics systems using soft computing methodology of Fuzzy Cognitive Maps

Abstract

Fuzzy Cognitive Maps (FCMs) is an abstract soft computing modeling methodology that has been applied in many areas quite successfully. In this paper we discuss its modeling applicability to complex logistics systems involved in an intermodal container terminal and the way it could represent and handle the vast amount of information by an abstract point of view based on a decentralized approach, where the supervisor of the system is modeled as an FCM. We also investigate its applicability as a metamodel of the intermodal terminal in a simulation-optimization framework. Experts have a key role in developing the FCM as they describe a general operational and behavioral model of the system using concepts for the main aspects of the system, and weighted directed edges to represent causality. On the other hand, when data is available, data driven approaches have also been proposed for the development of FCM models. The FCM representation and implementation is discussed to develop a behavioral model of any complex system mainly based on a hierarchical structure, as well as its use as a metamodel of the system.